We first describe a standard text-span-based RC task such as SQuAD [1]}. Given a supporting paragraph \(\mathcal {P} = \left\langle {p_1},{p_2},...,{p_M}\right\rangle \)  with \(M\)  tokens and a query \(\mathcal {Q} = \left\langle {q_1},{q_2},...,{q_L}\right\rangle \)  with \(L\)  tokens, the answer \(\mathcal {A} = \left\langle {p_{a^{s}}},{p_{{a^{s}} + 1}},...,{p_{a^{e}}}\right\rangle \)  is a text piece in the original paragraph. This task aims to find out the correct answer span \((a^{s},a^{e}), 0 \le a^{s} \le a^{e} \le M\) . It means that a model needs to predict two values: the start index and the end index of the answer span.
